1. Field of the Invention
The present invention relates to a method for noise reduction in a sequence of images.
2. Description of the Related Art
In dynamic digital radiography, image sequences of an object are generated in real time. During acquisition multiple, successive digital images or frames (frame images) are taken. Successive images are recorded e.g. by a digital radiography detector.
The present invention focuses on applications in which motion or immediate feedback are crucial, e.g. the temporal evolution in contrast studies or interventional fluoroscopy to guide and verify surgical actions.
Compared to static x-ray images, the dose per image or frame can be extremely low for the fluoroscopic image sequences. As a result the noise content in a single frame is much higher compared to static images. Therefore noise reduction is a major concern in the process of visualization enhancement of fluoroscopic image sequences.
Typically, spatio-temporal filtering techniques are used to reduce the noise by making use of the strong correlation between successive frames.
State-of-the-art algorithms use motion estimation to balance the strength of spatial and temporal noise filtering. In static image regions, temporal noise filtering preserves image details far better than spatial filtering. However temporal filtering can generate artefacts called motion blur in strongly moving scenes. State-of-the-art noise reduction algorithms try to avoid motion blur by reducing the strength of temporal filtering in favour of spatial filtering when motion is detected over the frames.
Detection of motion in fluoroscopic image sequences is extremely difficult due to the high noise content. Motion compensated spatio-temporal filtering often fails to detect motion accurately as the high noise content corrupts the image gradients used to control the filters.
Almost all the state-of-the-art noise reduction filters are implemented as multi-scale filters: these filters are applied to the wavelet or Laplacian pyramid representations of the frames. Modifying the multi-scale decompositions allows more filtering of the high frequency noise signals while preserving the mid and low frequency structure signals in the images.
It is an aspect of the present invention to provide a multi-scale temporal noise reduction method that does not require motion estimation.